class_docstr: Dataset containing sentences and their blocks for an inverse cloze task.
class_docstr_tok: ["Dataset","containing","sentences","and","their","blocks","for","an","inverse","cloze","task","."]
docstr: Get the IDs for an evidence block plus the title of the corresponding document
docstr_tok: ["Get","the","IDs","for","an","evidence","block","plus","the","title","of","the","corresponding","document"]
code: def get_block(self, start_idx, end_idx, doc_idx):
      """Get the IDs for an evidence block plus the title of the corresponding document"""
      block = [self.block_dataset[i] for i in range(start_idx, end_idx)]
      title = self.title_dataset[int(doc_idx)]
  
      block = list(itertools.chain(*block))[
          : self.max_seq_length - (3 + len(title))
      ]
      block_tokens, block_pad_mask = self.concat_and_pad_tokens(
          block, title
      )
  
      return block_tokens, block_pad_mask
  
file_path: megatron-lm/megatron/data/ict_dataset.py
imports: import itertools
  import random
  import numpy
  from torch.utils.data import Dataset
  from megatron import get_tokenizer
  from megatron import get_args
  from megatron.data.dataset_utils import get_indexed_dataset_
  from megatron.data.realm_dataset_utils import get_block_samples_mapping
label_desc: Use image node_id 4 for calling the ICTDataset obj's underlying member method code with example usage: obj.get_block(start_idx, end_idx, doc_idx) and returns: block_tokens,  block_pad_mask